The study analyzed the predictors of spatial determinants of rural poverty in developing countries using the case of Akwa Ibom State, Nigeria. With Yamane statistical technique, 400 households in 30 randomly sampled rural communities drawn from 19 out of 31 LGAs of the State were selected for oral interview using structured questionnaire complemented by field observations and focused group discussions to assess the indicators and predictors of poverty levels in the communities. Data on 28 poverty indicators and 14 determinants of rural poverty were obtained and analyzed using factor analysis and step-wise regression model. The factor analysis model engaged in analyzing the 28 poverty indicators yielded eight principal dimensions of rural poverty which accounted for 75.87 percent variation in the original 28 indicator variables. The step-wise regression model was used in analyzing the 14 predictors’ of rural poverty against each of the eight dimensions of rural poverty obtained from the factor scores of the analysis. The regression results revealed that rural poverty are mostly affected by spatial factors such as the communities distance to state capital, communities’ location, and other non-spatial factors such as availability of all day periodic market, household size, number of dependents’, household heads’ educational attainment and availability of electricity. Gender, marital status, and age of household heads are found to not significantly influence rural poverty levels.
Esin et al. (Wed,) studied this question.